Evaluation of Virtual Grid processed clinical pelvic radiographs

BACKGROUND

A physical scatter grid is not often used in pelvic bedside examinations. However, multiple studies regarding scatter correction software (SC SW) are available for mobile chest radiography but the results are unclear for pelvic radiography.

PURPOSE

We evaluated SC SW of Fujifilm (Virtual Grid) on gridless pelvic radiographs obtained from a human Thiel-embalmed body to investigate the potential of Virtual Grid in pelvic bedside examinations.

METHODS

Gridless, Virtual Grid, and physical grid pelvic radiographs of a female Thiel-embalmed body were collected with a broad range of tube loads. Different software (SW) grid ratios-6:1, 10:1, 13:1, 17:1, and 20:1-were applied on the gridless radiographs to investigate the image quality (IQ) improvement of 13 IQ criteria in a visual grading analysis (VGA) setup.

RESULTS

Gridless radiograph scores are significantly lower (p < 0.001) than Virtual Grid and physical grid scores obtained with the same tube load. Virtual Grid radiographs score better than gridless radiographs obtained with a higher tube load which makes a dose reduction possible. The averaged ratings of the IQ criteria processed with different SW ratios increase with increasing SW grid ratios. However, no statistically significant differences were found between the SW grid ratios. The scores of the physical grid radiographs are higher than those of the Virtual Grid radiographs when they are obtained with the same tube load.

CONCLUSION

We conclude that Virtual Grid with an SW ratio of 6:1 improves the IQ of gridless pelvic radiographs in such a manner that a dose reduction is possible. However, physical grid radiograph ratings are higher compared to those of Virtual Grid radiographs.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Declutter the MRI protocol tree: Managing and comparing sequence parameters of multiple clinical Siemens MRI systems

An MRI protocol tree on a clinical MRI system is a large database containing hundreds of protocols, each containing multiple sequences, and up to 900 parameters per sequence. Protocol variation between scan sessions or patients must be avoided as much as possible, as it may lead to financial loss and less than optimal outcomes for the patient. Without proper management, protocol variation and errors in MRI protocol trees are easily introduced and may remain undetected, leading to a cluttered protocol tree. This in turn reduces the efficiency of the radiological MRI workflow. We introduce a method and open-source software tools for managing MRI protocols on a sequence parameter level, which can detect deviations and variations in the protocol tree. It can be used offline, away from the scanner console, without disturbing the clinical workflow. These tools help to create a standardized protocol library across multiple MRI scanners, reducing variation and errors, enabling radiology departments to create optimal value for the patient and institution.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol

INTRODUCTION

Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD).

METHODS AND ANALYSIS

DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies.

ETHICS AND DISSEMINATION

Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Effect of Acetylcholinesterase Inhibitors on Cerebral Perfusion and Cognition: A Systematic Review

BACKGROUND

Perfusion imaging has the potential to identify neurodegenerative disorders in a preclinical stage. However, to correctly interpret perfusion-derived parameters, the impact of perfusion modifiers should be evaluated.

OBJECTIVE

In this systematic review, the impact of acute and chronic intake of four acetylcholinesterase inhibitors (AChEIs) on cerebral perfusion in adults was investigated: physostigmine, donepezil, galantamine, and rivastigmine.

RESULTS

Chronic AChEI treatment results in an increase of cerebral perfusion in treatment-responsive patients with Alzheimer's disease, dementia with Lewy bodies, and Parkinson's disease dementia in the frontal, parietal, temporal, and occipital lobes, as well as the cingulate gyrus. These effects appear to be temporary, dose-related, and consistent across populations and different AChEI types. On the contrary, further perfusion decline was reported in patients not receiving AChEIs or not responding to the treatment.

CONCLUSION

AChEIs appear to be a potential perfusion modifier in neurodegenerative patients. More research focused on quantitative perfusion in both patients with and without a cholinergic deficit is needed to draw conclusions on whether AChEI intake should be considered when analyzing perfusion data.

Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging

This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.

Imaging blood-brain barrier dysfunction: A state-of-the-art review from a clinical perspective

The blood-brain barrier (BBB) consists of specialized cells that tightly regulate the in- and outflow of molecules from the blood to brain parenchyma, protecting the brain's microenvironment. If one of the BBB components starts to fail, its dysfunction can lead to a cascade of neuroinflammatory events leading to neuronal dysfunction and degeneration. Preliminary imaging findings suggest that BBB dysfunction could serve as an early diagnostic and prognostic biomarker for a number of neurological diseases. This review aims to provide clinicians with an overview of the emerging field of BBB imaging in humans by answering three key questions: (1. Disease) In which diseases could BBB imaging be useful? (2. Device) What are currently available imaging methods for evaluating BBB integrity? And (3. Distribution) what is the potential of BBB imaging in different environments, particularly in resource limited settings? We conclude that further advances are needed, such as the validation, standardization and implementation of readily available, low-cost and non-contrast BBB imaging techniques, for BBB imaging to be a useful clinical biomarker in both resource-limited and well-resourced settings.

ASL-BIDS, the brain imaging data structure extension for arterial spin labeling

Arterial spin labeling (ASL) is a non-invasive MRI technique that allows for quantitative measurement of cerebral perfusion. Incomplete or inaccurate reporting of acquisition parameters complicates quantification, analysis, and sharing of ASL data, particularly for studies across multiple sites, platforms, and ASL methods. There is a strong need for standardization of ASL data storage, including acquisition metadata. Recently, ASL-BIDS, the BIDS extension for ASL, was developed and released in BIDS 1.5.0. This manuscript provides an overview of the development and design choices of this first ASL-BIDS extension, which is mainly aimed at clinical ASL applications. Discussed are the structure of the ASL data, focussing on storage order of the ASL time series and implementation of calibration approaches, unit scaling, ASL-related BIDS fields, and storage of the labeling plane information. Additionally, an overview of ASL-BIDS compatible conversion and ASL analysis software and ASL example datasets in BIDS format is provided. We anticipate that large-scale adoption of ASL-BIDS will improve the reproducibility of ASL research.

The Impact of Accelerated HF-rTMS on Canine Brain Metabolism: An [18F]-FDG PET Study in Healthy Beagles

Background

Repetitive transcranial magnetic stimulation (rTMS) has been proven to be a useful tool for the treatment of several severe neuropsychiatric disorders. Accelerated (a)rTMS protocols may have the potential to result in faster clinical improvements, but the effects of such accelerated paradigms on brain function remain to be elucidated.

Objectives

This sham-controlled arTMS study aimed to evaluate the immediate and delayed effects of accelerated high frequency rTMS (aHF-rTMS) on glucose metabolism in healthy beagle dogs when applied over the left frontal cortex.

Methods

Twenty-four dogs were randomly divided into four unequal groups: five active (n = 8)/ sham (n = 4) stimulation sessions (five sessions in 1 day), 20 active (n = 8)/ sham (n = 4) stimulation sessions (five sessions/ day for 4 days), respectively. [¹⁸F] FDG PET scans were obtained at baseline, 24 h poststimulation, after 1 and 3 months post the last stimulation session. We explicitly focused on four predefined regions of interest (left/right prefrontal cortex and left/right hippocampus).

Results

One day of active aHF-rTMS- and not sham- significantly increased glucose metabolism 24 h post-active stimulation in the left frontal cortex only. Four days of active aHF-rTMS only resulted in a nearly significant metabolic decrease in the left hippocampus after 1 month.

Conclusions

Like in human psychiatric disorders, active aHF-rTMS in healthy beagles modifies glucose metabolism, although differently immediately or after 1 month post stimulation. aHF-rTMS may be also a valid option to treat mentally disordered dogs.

The costs and benefits of estimating T1 of tissue alongside cerebral blood flow and arterial transit time in pseudo-continuous arterial spin labeling

Multi-post-labeling-delay pseudo-continuous arterial spin labeling (multi-PLD PCASL) allows for absolute quantification of the cerebral blood flow (CBF) as well as the arterial transit time (ATT). Estimating these perfusion parameters from multi-PLD PCASL data is a non-linear inverse problem, which is commonly tackled by fitting the single-compartment model (SCM) for PCASL, with CBF and ATT as free parameters. The longitudinal relaxation time of tissue T_1t is an important parameter in this model, as it governs the decay of the perfusion signal entirely upon entry in the imaging voxel. Conventionally, T_1t is fixed to a population average. This approach can cause CBF quantification errors, as T_1t can vary significantly inter- and intra-subject. This study compares the impact on CBF quantification, in terms of accuracy and precision, of either fixing T_1t , the conventional approach, or estimating it alongside CBF and ATT. It is shown that the conventional approach can cause a significant bias in CBF. Indeed, simulation experiments reveal that if T_1t is fixed to a value that is 10% off its true value, this may already result in a bias of 15% in CBF. On the other hand, as is shown by both simulation and real data experiments, estimating T_1t along with CBF and ATT results in a loss of CBF precision of the same order, even if the experiment design is optimized for the latter estimation problem. Simulation experiments suggest that an optimal balance between accuracy and precision of CBF estimation from multi-PLD PCASL data can be expected when using the two-parameter estimator with a fixed T_1t value between population averages of T_1t and the longitudinal relaxation time of blood T_1b .

Impact of a code stroke protocol on the door-to-needle time for IV thrombolysis: a feasibility study

INTRODUCTION

Stroke is a development of an acute focal neurological deficit with an ischemic or hemorrhagic origin. Thrombolysis within 4.5 h of ischemic stroke onset improves outcome. Guidelines recommend administration of intravenous recombinant tissue plasminogen activator within 60 min upon arrival at the hospital, meaning the door-to-needle time (DNT) should be less than 60 min. In this study, a stroke protocol was introduced at the emergency department of the Ghent University Hospital with a primary goal to shorten the DNT.

METHODOLOGY

This study was an uncontrolled before-after cohort study. A 'Code Stroke' protocol (CSP) was implemented and the results from the pre-code stroke protocol period (Pre-CSP period, from 15 August 2016 until 5 March 2017) were compared with the results from the post-code stroke protocol period (Post-CSP period, from 6 March 2017 until 16 July 2017).

RESULTS

The median DNT decreased significantly from 57 min in the Pre-CSP period to 33 min in the Post-CSP period (p < 0.001). The door-to-triage time (DTT), triage-to-emergency physician time (TET), emergency physician-to-CT time (ECT) and CT-to needle time (CNT) decreased significantly Post-CSP compared to Pre-CSP. When adjusting the results for other variables that might have an influence on these time intervals, the TET, ECT and CNT also decreased significantly. There was a statistically significant effect of the implementation of the CSP on the number of patients treated with a DNT within 20, 30, 45 and 60 min (p = 0.008).

CONCLUSION

A significant decrease in DNT can be achieved with the implementation of this stroke protocol.

ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Supporting measurements or more averages? How to quantify cerebral blood flow most reliably in 5 minutes by arterial spin labeling

Purpose

To determine whether sacrificing part of the scan time of pseudo‐continuous arterial spin labeling (PCASL) for measurement of the labeling efficiency and blood T1 is beneficial in terms of CBF quantification reliability.

Methods

In a simulation framework, 5‐minute scan protocols with different scan time divisions between PCASL data acquisition and supporting measurements were evaluated in terms of CBF estimation variability across both noise and ground truth parameter realizations taken from the general population distribution. The entire simulation experiment was repeated for a single‐post‐labeling delay (PLD), multi‐PLD, and free‐lunch time‐encoded (te‐FL) PCASL acquisition strategy. Furthermore, a real data study was designed for preliminary validation.

Results

For the considered population statistics, measuring the labeling efficiency and the blood T1 proved beneficial in terms of CBF estimation variability for any distribution of the 5‐minute scan time compared to only acquiring ASL data. Compared to single‐PLD PCASL without support measurements as recommended in the consensus statement, a 26%, 33%, and 42% reduction in relative CBF estimation variability was found for optimal combinations of supporting measurements with single‐PLD, free‐lunch, and multi‐PLD PCASL data acquisition, respectively. The benefit of taking the individual variation of blood T1 into account was also demonstrated in the real data experiment.

Conclusions

Spending time to measure the labeling efficiency and the blood T1 instead of acquiring more averages of the PCASL data proves to be advisable for robust CBF quantification in the general population.

Optimization of PET protocol and interrater reliability of 18F-PSMA-11 imaging of prostate cancer

BACKGROUND

Several scan parameters for PET imaging with 18F-PSMA-11 such as dosage, acquisition time and scan duration were evaluated to determine the most appropriate scan protocol, as well as the effect of furosemide administration on lesion visualization. Forty-four patients were randomly assigned to a dosage group (2.0 ± 0.2 or 4.0 ± 0.4 MBq/kg 18F-PSMA-11). All patients received a full-body PET/CT 1 h and 3 h after radiotracer injection with a scan duration of 3 min/bed position. For comparison of the scan duration, images were reconstructed for 1.5 and 3 min/bed position. Patients were intravenously administered 0.5 mg/kg furosemide with a maximum dose of 40 mg. To evaluate the furosemide effect, 22 additional patients were recruited and received one full-body PET/CT 1 h after administration of 2.0 ± 0.2 MBq/kg 18F-PSMA-11 with a scan duration of 3 min/bed position. To this group, no furosemide was administered. Images were scored on image quality using a 7-point scale and each suspicious lesion was described. To assess interrater reliability, two nuclear physicians scored all scans independently and described all observed suspicious lesions.

RESULTS

The 4 MBq/kg group received for all reconstructed images (60 min p.i., 1.5 and 3 min/bed position and 180 min p.i., 1.5 and 3 min/bed position) the highest median image quality score compared to the 2 MBq/kg group (p values < 0.01). When comparing all reconstructed images, the highest image quality score was given to images at 60 min p.i., 3 min/bed position for both dosage groups (score 5 and 6 for 2 and 4 MBq/kg, respectively). The addition of furosemide administration decreased the interference score with one point (p = 0.01106) and facilitated the evaluation of lesions in proximity to the ureters. The interrater reliability for the comparison of each lesion separately after more than 40 18F-PSMA-11 scan readings showed an increasing κ value from 0.78 (95% CI, 0.65-0.92) to 0.94 (95% CI, 0.87-1).

CONCLUSION

Although the results indicate an administered activity of 4.0 ± 0.4 MBq/kg, preference will be given to 2.0 ± 0.2 MBq/kg due to the small difference in absolute score (max 1 point) and the ALARA principle. For evaluation of lesions in proximity to the ureters, the co-administration of a diuretic can be useful. The increase of the κ value from 0.78 to 0.94 suggests a learning curve in the interpretation of 18F-PSMA-11 images.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT03573011. Retrospectively registered 28 June 2018.

The use of Thiel embalmed human cadavers for retrograde injection and visualization of the lymphatic system

In order to provide an alternative for fresh frozen specimens to map the lymphatic system, the possibility of using Thiel embalmed specimens for this purpose was explored. The thoracic duct was used to investigate if retrograde injection of contrast agent was possible in Thiel embalmed specimens and to verify up to which diameter lymphatic vessels could be reconstructed and rendered in 3D, after CT scanning. 3D renderings were used for digital diameter measurement, to determine the smallest lymphatic diameter that could still be visualized on CT. Finally, the contrast agent concentration was adapted based on the findings during image reconstruction and 3D rendering. All Thiel embalmed specimens proved suitable for retrograde injection of contrast agent into the thoracic duct and all 3D renderings perfectly overlapped with the dissection pictures. The smallest diameter of contrast filled lymphatics that could be reconstructed and rendered in 3D was 0.23 mm. Increasing the concentration of barium sulfate from 10 to 50% reduced the postprocessing time needed to render a "clean" 3D structure, following automatic segmentation based on grey values, by 95%. The authors would recommend the use of Thiel embalmed specimens for mapping the lymphatic system, as these specimens do not show the rapid putrefaction that occurs in fresh frozen specimens, thus greatly facilitating experimental planning.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Joint coordinate system for biomechanical analysis of the sacroiliac joint

Sacroiliac joint (SIJ) biomechanics have been described in both in vitro and in vivo studies. A standard for joint coordinate systems has been created by the International Society of Biomechanics for most of the joints in the human body. However, a standardized joint coordinate system for sacroiliac joint motion analysis is currently still lacking. This impedes the comparison across studies and hinders communication among scientists and clinicians. As SIJ motion is reported to be quite limited, a proper standardization and reproducibility of this procedure is essential for the interpretation of future biomechanical SIJ studies. This paper proposes a joint coordinate system for the analysis of sacroiliac joint motion, based on the procedure developed by Grood and Suntay, using semi-automated anatomical landmarks on 3D joint surfaces. This coordinate system offers high inter-rater reliability and aspires to a more intuitive representation of biomechanical data, as it is aligned with SIJ articular surfaces. This study aims to encourage further reflection and debate on biomechanical data representation, in order to facilitate interpretation of SIJ biomechanics and improve communication between researchers and clinicians. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.

Automated Assessment of Bone Age Using Deep Learning and Gaussian Process Regression

Bone age is an essential measure of skeletal maturity in children with growth disorders. It is typically assessed by a trained physician using radiographs of the hand and a reference model. However, it has been described that the reference models leave room for interpretation leading to a large inter-observer and intra-observer variation. In this work, we explore a novel method for automated bone age assessment to assist physicians with their estimation. It consists of a powerful combination of deep learning and Gaussian process regression. Using this combination, sensitivity of the deep learning model to rotations and flips of the input images can be exploited to increase overall predictive performance compared to only using the deep learning network. We validate our approach retrospectively on a set of 12611 radiographs of patients between 0 and 19 years of age.

A New ROI-Based performance evaluation method for image denoising using the Squared Eigenfunctions of the Schrödinger Operator

In this paper a new Region Of Interest (ROI) characterization for image denoising performance evaluation is proposed. This technique consists of balancing the contrast between the dark and bright ROIs, in Magnetic Resonance (MR) images, to track the noise removal. It achieves an optimal compromise between removal of noise and preservation of image details. The ROI technique has been tested using synthetic MRI images from the BrainWeb database. Moreover, it has been applied to a recently developed denoising method called Semi-Classical Signal Analysis (SCSA). The SCSA decomposes the image into the squared eigenfunctions of the Schrödinger operator where a soft threshold $h$ is used to remove the noise. The results obtained using real MRI data suggest that this method is suitable for real medical image processing evaluation where the noise-free image is not available.

Reduction of Acquisition time using Partition of the sIgnal Decay in Spectroscopic Imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the sIgnal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R = acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R = 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor √R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging.

Variability of physiological brain perfusion in healthy subjects - A systematic review of modifiers. Considerations for multi-center ASL studies

Quantitative measurements of brain perfusion are influenced by perfusion-modifiers. Standardization of measurement conditions and correction for important modifiers is essential to improve accuracy and to facilitate the interpretation of perfusion-derived parameters. An extensive literature search was carried out for factors influencing quantitative measurements of perfusion in the human brain unrelated to medication use. A total of 58 perfusion modifiers were categorized into four groups. Several factors (e.g., caffeine, aging, and blood gases) were found to induce a considerable effect on brain perfusion that was consistent across different studies; for other factors, the modifying effect was found to be debatable, due to contradictory results or lack of evidence. Using the results of this review, we propose a standard operating procedure, based on practices already implemented in several research centers. Also, a theory of 'deep MRI physiotyping' is inferred from the combined knowledge of factors influencing brain perfusion as a strategy to reduce variance by taking both personal information and the presence or absence of perfusion modifiers into account. We hypothesize that this will allow to personalize the concept of normality, as well as to reach more rigorous and earlier diagnoses of brain disorders.

Consensus statement on current and emerging methods for the diagnosis and evaluation of cerebrovascular disease

Cerebrovascular disease (CVD) remains a leading cause of death and the leading cause of adult disability in most developed countries. This work summarizes state-of-the-art, and possible future, diagnostic and evaluation approaches in multiple stages of CVD, including (i) visualization of sub-clinical disease processes, (ii) acute stroke theranostics, and (iii) characterization of post-stroke recovery mechanisms. Underlying pathophysiology as it relates to large vessel steno-occlusive disease and the impact of this macrovascular disease on tissue-level viability, hemodynamics (cerebral blood flow, cerebral blood volume, and mean transit time), and metabolism (cerebral metabolic rate of oxygen consumption and pH) are also discussed in the context of emerging neuroimaging protocols with sensitivity to these factors. The overall purpose is to highlight advancements in stroke care and diagnostics and to provide a general overview of emerging research topics that have potential for reducing morbidity in multiple areas of CVD.

Presence of the posterior pituitary bright spot sign on MRI in the general population: a comparison between 1.5 and 3T MRI and between 2D-T1 spin-echo- and 3D-T1 gradient-echo sequences

PURPOSE

To describe the prevalence of the posterior pituitary bright spot (PPBS) in the general population on 1.5 and 3T MRI examinations and on 2D-T1 spin-echo (SE) and 3D-T1 gradient-echo (GE) sequences.

MATERIALS AND METHODS

1017 subjects who received an MRI of the brain for aspecific neurological complaints were included. MRI was performed on 1.5T in 64.5% and on 3T in 35.5% of subjects. Presence of the PPBS was evaluated on sagittal 2D T1-SE echo images with slice thickness 3 mm in 67.5% and on sagittal 3D T1-GE with slice thickness 0.9 mm in 32.5% of subjects.

RESULTS

The PPBS was detectable in 95.9% of subjects. After correction for sex and age, no statistically significant difference could be seen concerning PPBS detection between 1.5 and 3T MRI examinations (p = 0.533), nor between 2D T1-SE and 3D T1-GE sequences (p = 0.217). There was a statistically significant association between increasing age and the absence of the PPBS (p < 0.001). The PPBS could not be identified in 6.2% of male subjects, compared to 2.2% of female subjects (p = 0.01).

DISCUSSION

Absence of the PPBS can be seen in 4.1% of patients undergoing MRI of the brain for non-endocrinological reasons. Neither field-strength nor the use of a thick-sliced 2D T1-SE versus a thin-sliced 3D T1-GE sequence influenced the detectability of the PPBS. There is a statistically significant association between increasing age and male sex and the absence of the PPBS.

Estimating the Patient-specific Dose to the Thyroid and Breasts and Overall Risk in Chest CT When Using Organ-based Tube Current Modulation

Purpose To assess the potential dose reduction to the thyroid and breasts in chest computed tomography (CT) with organ-based tube current modulation (OBTCM). Materials and Methods In this retrospective study (from January 2015 to December 2016), the location of the breasts with respect to the reduced tube current zone was determined. With Monte Carlo simulations, patient-specific dose distributions of chest CT scans were calculated for 50 female patients (mean age, 53.7 years ± 17.5; range, 20-80 years). The potential dose reduction with OBTCM was assessed. In addition, simulations of clinical OBTCM scans were made for 17 of the 50 female patients (mean age, 43.8 years ± 17.1; range, 20-69 years). Posterior organs in the field of view were analyzed and lifetime attributable risk (LAR) of cancer incidence and mortality was estimated. Image quality between standard CT and OBTCM scans was compared. Results No women had all breast tissue within the reduced tube current zone. Dose reductions of 18% in the thyroid and 9% in the breasts were observed, whereas the doses in lung, liver, and kidney were 17%, 11%, and 26% higher. Overall, the LAR for cancer incidence was not significantly different between conventional and OBTCM scanning (P = .06). Image quality improved with OBTCM (P < .002). Conclusion The potential benefit of OBTCM to the female breast in chest CT is overestimated because of a limited reduced tube current zone; despite a 9% dose reduction to the female breast, posterior organs will absorb up to 26% more radiation, resulting in no reduction in radiation-induced malignancies. ^© RSNA, 2018.

The successive projection algorithm as an initialization method for brain tumor segmentation using non-negative matrix factorization

Non-negative matrix factorization (NMF) has become a widely used tool for additive parts-based analysis in a wide range of applications. As NMF is a non-convex problem, the quality of the solution will depend on the initialization of the factor matrices. In this study, the successive projection algorithm (SPA) is proposed as an initialization method for NMF. SPA builds on convex geometry and allocates endmembers based on successive orthogonal subspace projections of the input data. SPA is a fast and reproducible method, and it aligns well with the assumptions made in near-separable NMF analyses. SPA was applied to multi-parametric magnetic resonance imaging (MRI) datasets for brain tumor segmentation using different NMF algorithms. Comparison with common initialization methods shows that SPA achieves similar segmentation quality and it is competitive in terms of convergence rate. Whereas SPA was previously applied as a direct endmember extraction tool, we have shown improved segmentation results when using SPA as an initialization method, as it allows further enhancement of the sources during the NMF iterative procedure.

Semi-automated brain tumor segmentation on multi-parametric MRI using regularized non-negative matrix factorization

Background

Segmentation of gliomas in multi-parametric (MP-)MR images is challenging due to their heterogeneous nature in terms of size, appearance and location. Manual tumor segmentation is a time-consuming task and clinical practice would benefit from (semi-) automated segmentation of the different tumor compartments.

Methods

We present a semi-automated framework for brain tumor segmentation based on non-negative matrix factorization (NMF) that does not require prior training of the method. L1-regularization is incorporated into the NMF objective function to promote spatial consistency and sparseness of the tissue abundance maps. The pathological sources are initialized through user-defined voxel selection. Knowledge about the spatial location of the selected voxels is combined with tissue adjacency constraints in a post-processing step to enhance segmentation quality. The method is applied to an MP-MRI dataset of 21 high-grade glioma patients, including conventional, perfusion-weighted and diffusion-weighted MRI. To assess the effect of using MP-MRI data and the L1-regularization term, analyses are also run using only conventional MRI and without L1-regularization. Robustness against user input variability is verified by considering the statistical distribution of the segmentation results when repeatedly analyzing each patient’s dataset with a different set of random seeding points.

Results

Using L1-regularized semi-automated NMF segmentation, mean Dice-scores of 65%, 74 and 80% are found for active tumor, the tumor core and the whole tumor region. Mean Hausdorff distances of 6.1 mm, 7.4 mm and 8.2 mm are found for active tumor, the tumor core and the whole tumor region. Lower Dice-scores and higher Hausdorff distances are found without L1-regularization and when only considering conventional MRI data.

Conclusions

Based on the mean Dice-scores and Hausdorff distances, segmentation results are competitive with state-of-the-art in literature. Robust results were found for most patients, although careful voxel selection is mandatory to avoid sub-optimal segmentation.

Proximal aortic stiffening in Turner patients may be present before dilation can be detected: a segmental functional MRI study

BACKGROUND

To study segmental structural and functional aortic properties in Turner syndrome (TS) patients. Aortic abnormalities contribute to increased morbidity and mortality of women with Turner syndrome. Cardiovascular magnetic resonance (CMR) allows segmental study of aortic elastic properties.

METHOD

We performed Pulse Wave Velocity (PWV) and distensibility measurements using CMR of the thoracic and abdominal aorta in 55 TS-patients, aged 13-59y, and in a control population (n = 38;12-58y). We investigated the contribution of TS on aortic stiffness in our entire cohort, in bicuspid (BAV) versus tricuspid (TAV) aortic valve-morphology subgroups, and in the younger and older subgroups.

RESULTS

Differences in aortic properties were only seen at the most proximal aortic level. BAV Turner patients had significantly higher PWV, compared to TAV Turner (p = 0.014), who in turn had significantly higher PWV compared to controls (p = 0.010). BAV Turner patients had significantly larger ascending aortic (AA) luminal area and lower AA distensibility compared to both controls (all p < 0.01) and TAV Turner patients. TAV Turner had similar AA luminal areas and AA distensibility compared to Controls. Functional changes are present in younger and older Turner subjects, whereas ascending aortic dilation is prominent in older Turner patients. Clinically relevant dilatation (TAV and BAV) was associated with reduced distensibility.

CONCLUSION

Aortic stiffening and dilation in TS affects the proximal aorta, and is more pronounced, although not exclusively, in BAV TS patients. Functional abnormalities are present at an early age, suggesting an aortic wall disease inherent to the TS. Whether this increased stiffness at young age can predict later dilatation needs to be studied longitudinally.

"Unforgettable" - a pictorial essay on anatomy and pathology of the hippocampus

Abstract

The hippocampus is a small but complex anatomical structure that plays an important role in spatial and episodic memory. The hippocampus can be affected by a wide range of congenital variants and degenerative, inflammatory, vascular, tumoral and toxic-metabolic pathologies. Magnetic resonance imaging is the preferred imaging technique for evaluating the hippocampus. The main indications requiring tailored imaging sequences of the hippocampus are medically refractory epilepsy and dementia. The purpose of this pictorial review is threefold: (1) to review the normal anatomy of the hippocampus on MRI; (2) to discuss the optimal imaging strategy for the evaluation of the hippocampus; and (3) to present a pictorial overview of the most common anatomic variants and pathologic conditions affecting the hippocampus.

Teaching points

• Knowledge of normal hippocampal anatomy helps recognize anatomic variants and hippocampal pathology.

• Refractory epilepsy and dementia are the main indications requiring dedicated hippocampal imaging.

• Pathologic conditions centered in and around the hippocampus often have similar imaging features.

• Clinical information is often necessary to come to a correct diagnosis or an apt differential.

Spectral data de-noising using semi-classical signal analysis: application to localized MRS

In this paper, we propose a new post-processing technique called semi-classical signal analysis (SCSA) for MRS data de-noising. Similar to Fourier transformation, SCSA decomposes the input real positive MR spectrum into a set of linear combinations of squared eigenfunctions equivalently represented by localized functions with shape derived from the potential function of the Schrödinger operator. In this manner, the MRS spectral peaks represented as a sum of these 'shaped like' functions are efficiently separated from noise and accurately analyzed. The performance of the method is tested by analyzing simulated and real MRS data. The results obtained demonstrate that the SCSA method is highly efficient in localized MRS data de-noising and allows for an accurate data quantification.

Comparison of unsupervised classification methods for brain tumor segmentation using multi-parametric MRI

Tumor segmentation is a particularly challenging task in high-grade gliomas (HGGs), as they are among the most heterogeneous tumors in oncology. An accurate delineation of the lesion and its main subcomponents contributes to optimal treatment planning, prognosis and follow-up. Conventional MRI (cMRI) is the imaging modality of choice for manual segmentation, and is also considered in the vast majority of automated segmentation studies. Advanced MRI modalities such as perfusion-weighted imaging (PWI), diffusion-weighted imaging (DWI) and magnetic resonance spectroscopic imaging (MRSI) have already shown their added value in tumor tissue characterization, hence there have been recent suggestions of combining different MRI modalities into a multi-parametric MRI (MP-MRI) approach for brain tumor segmentation. In this paper, we compare the performance of several unsupervised classification methods for HGG segmentation based on MP-MRI data including cMRI, DWI, MRSI and PWI. Two independent MP-MRI datasets with a different acquisition protocol were available from different hospitals. We demonstrate that a hierarchical non-negative matrix factorization variant which was previously introduced for MP-MRI tumor segmentation gives the best performance in terms of mean Dice-scores for the pathologic tissue classes on both datasets.

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Unsupervised classification algorithms are applied for brain tumor segmentation on multi-parametric MRI datasets.

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Reported mean Dice-scores are in the range of state-of-the-art segmentation algorithms.

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Hierarchical NMF obtained the best segmentation results in terms of mean Dice-scores for most of the tissue classes.

In Vivo Magnetic Resonance Imaging and 31P Spectroscopy of Large Human Brain Tumours at 1.5 Tesla

31P MR spectroscopy of human brain tumours is one feature of magnetic resonance imaging. Eight patients with large superficial brain tumours and eight healthy volunteers were examined with 31P spectroscopy using an 8 cm surface coil for volume selection. Seven frequencies were resolved in our spectra. The spectra from patients with brain tumours showed a great scatter, but generally they overlapped those obtained in normal brain tissue. No characteristic pattern of the spectra was seen in the tumours. One patient with a metastasis from a small cell carcinoma of the lung was examined before and after chemotherapy. The spectra showed considerable changes during chemotherapy. It is concluded that 31P spectroscopy using surface coils is of limited value for tumour characterization, but may add useful information in monitoring the effect of chemotherapy.

Optimal number of atlases and label fusion for automatic multi-atlas-based brachial plexus contouring in radiotherapy treatment planning

BACKGROUND

The present study aimed to define the optimal number of atlases for automatic multi-atlas-based brachial plexus (BP) segmentation and to compare Simultaneous Truth and Performance Level Estimation (STAPLE) label fusion with Patch label fusion using the ADMIRE® software. The accuracy of the autosegmentations was measured by comparing all of the generated autosegmentations with the anatomically validated gold standard segmentations that were developed using cadavers.

MATERIALS AND METHODS

Twelve cadaver computed tomography (CT) atlases were used for automatic multi-atlas-based segmentation. To determine the optimal number of atlases, one atlas was selected as a patient and the 11 remaining atlases were registered onto this patient using a deformable image registration algorithm. Next, label fusion was performed by using every possible combination of 2 to 11 atlases, once using STAPLE and once using Patch. This procedure was repeated for every atlas as a patient. The similarity of the generated automatic BP segmentations and the gold standard segmentation was measured by calculating the average Dice similarity (DSC), Jaccard (JI) and True positive rate (TPR) for each number of atlases. These similarity indices were compared for the different number of atlases using an equivalence trial and for the two label fusion groups using an independent sample-t test.

RESULTS

DSC's and JI's were highest when using nine atlases with both STAPLE (average DSC = 0,532; JI = 0,369) and Patch (average DSC = 0,530; JI = 0,370). When comparing both label fusion algorithms using 9 atlases for both, DSC and JI values were not significantly different. However, significantly higher TPR values were achieved in favour of STAPLE (p < 0,001). When fewer than four atlases were used, STAPLE produced significantly lower DSC, JI and TPR values than did Patch (p = 0,0048).

CONCLUSIONS

Using 9 atlases with STAPLE label fusion resulted in the most accurate BP autosegmentations (average DSC = 0,532; JI = 0,369 and TPR = 0,760). Only when using fewer than four atlases did the Patch label fusion results in a significantly more accurate autosegmentation than STAPLE.

The effect of morphometric atlas selection on multi-atlas-based automatic brachial plexus segmentation

Purpose

The present study aimed to measure the effect of a morphometric atlas selection strategy on the accuracy of multi-atlas-based BP autosegmentation using the commercially available software package ADMIRE® and to determine the optimal number of selected atlases to use. Autosegmentation accuracy was measured by comparing all generated automatic BP segmentations with anatomically validated gold standard segmentations that were developed using cadavers.

Materials and methods

Twelve cadaver computed tomography (CT) atlases were included in the study. One atlas was selected as a patient in ADMIRE®, and multi-atlas-based BP autosegmentation was first performed with a group of morphometrically preselected atlases. In this group, the atlases were selected on the basis of similarity in the shoulder protraction position with the patient. The number of selected atlases used started at two and increased up to eight. Subsequently, a group of randomly chosen, non-selected atlases were taken. In this second group, every possible combination of 2 to 8 random atlases was used for multi-atlas-based BP autosegmentation. For both groups, the average Dice similarity coefficient (DSC), Jaccard index (JI) and Inclusion index (INI) were calculated, measuring the similarity of the generated automatic BP segmentations and the gold standard segmentation. Similarity indices of both groups were compared using an independent sample t-test, and the optimal number of selected atlases was investigated using an equivalence trial.

Results

For each number of atlases, average similarity indices of the morphometrically selected atlas group were significantly higher than the random group (p < 0,05). In this study, the highest similarity indices were achieved using multi-atlas autosegmentation with 6 selected atlases (average DSC = 0,598; average JI = 0,434; average INI = 0,733).

Conclusions

Morphometric atlas selection on the basis of the protraction position of the patient significantly improves multi-atlas-based BP autosegmentation accuracy. In this study, the optimal number of selected atlases used was six, but for definitive conclusions about the optimal number of atlases and to improve the autosegmentation accuracy for clinical use, more atlases need to be included.

The Vulnerability to Suicidal Behavior is Associated with Reduced Connectivity Strength

Suicidal behavior constitutes a major public health problem. Based on the stress–diathesis model, biological correlates of a diathesis might help to predict risk after stressor-exposure. Structural changes in cortical and subcortical areas and their connections have increasingly been linked with the diathesis. The current study identified structural network changes associated with a diathesis using a whole-brain approach by examining the structural connectivity between regions in euthymic suicide attempters (SA). In addition, the association between connectivity measures, clinical and genetic characteristics was investigated. We hypothesized that SA showed lower connectivity strength, associated with an increased severity of general clinical characteristics and an elevated expression of short alleles in serotonin polymorphisms. Thirteen euthymic SA were compared with fifteen euthymic non-attempters and seventeen healthy controls (HC). Clinical characteristics and three serotonin-related genetic polymorphisms were assessed. Diffusion MRI together with anatomical scans were administered. Preprocessing was performed using Explore DTI. Whole brain tractography of the diffusion-weighted images was followed by a number of streamlines-weighted network analysis using NBS. The network analysis revealed decreased connectivity strength in SA in the connections between the left olfactory cortex and left anterior cingulate gyrus. Furthermore, SA had increased suicidal ideation, hopelessness and self-reported depression, but did not show any differences for the genetic polymorphisms. Finally, lower connectivity strength between the right calcarine fissure and the left middle occipital gyrus was associated with increased trait anxiety severity (r_s = −0.78, p < 0.01) and hopelessness (r_s = −0.76, p < 0.01). SA showed differences in white matter network connectivity strength associated with clinical characteristics. Together, these variables could play an important role in predicting suicidal behavior.

Correlation of clinical and physical-technical image quality in chest CT: a human cadaver study applied on iterative reconstruction

Background

The first aim of this study was to evaluate the correlation between clinical and physical-technical image quality applied to different strengths of iterative reconstruction in chest CT images using Thiel cadaver acquisitions and Catphan images. The second aim was to determine the potential dose reduction of iterative reconstruction compared to conventional filtered back projection based on different clinical and physical-technical image quality parameters.

Methods

Clinical image quality was assessed using three Thiel embalmed human cadavers. A Catphan phantom was used to assess physical-technical image quality parameters such as noise, contrast-detail and contrast-to-noise ratio (CNR).

Both Catphan and chest Thiel CT images were acquired on a multislice CT scanner at 120 kVp and 0.9 pitch. Six different refmAs settings were applied (12, 30, 60, 90, 120 and 150refmAs) and each scan was reconstructed using filtered back projection (FBP) and iterative reconstruction (SAFIRE) algorithms (1,3 and 5 strengths) using a sharp kernel, resulting in 24 image series. Four radiologists assessed the clinical image quality, using a visual grading analysis (VGA) technique based on the European Quality Criteria for Chest CT.

Results

Correlation coefficients between clinical and physical-technical image quality varied from 0.88 to 0.92, depending on the selected physical-technical parameter. Depending on the strength of SAFIRE, the potential dose reduction based on noise, CNR and the inverse image quality figure (IQF_inv) varied from 14.0 to 67.8 %, 16.0 to 71.5 % and 22.7 to 50.6 % respectively. Potential dose reduction based on clinical image quality varied from 27 to 37.4 %, depending on the strength of SAFIRE.

Conclusion

Our results demonstrate that noise assessments in a uniform phantom overestimate the potential dose reduction for the SAFIRE IR algorithm. Since the IQF_inv based dose reduction is quite consistent with the clinical based dose reduction, an optimised contrast-detail phantom could improve the use of contrast-detail analysis for image quality assessment in chest CT imaging. In conclusion, one should be cautious to evaluate the performance of CT equipment taking into account only physical-technical parameters as noise and CNR, as this might give an incomplete representation of the actual clinical image quality performance.

Exercise training and Beta-alanine-induced muscle carnosine loading

Purpose

Beta-alanine (BA) supplementation has been shown to augment muscle carnosine concentration, thereby promoting high-intensity (HI) exercise performance. Trained muscles of athletes have a higher increase in carnosine concentration after BA supplementation compared to untrained muscles, but it remains to be determined whether this is due to an accumulation of acute exercise effects or to chronic adaptations from prior training. The aim of the present study was to investigate whether high-volume (HV) and/or HI exercise can improve BA-induced carnosine loading in untrained subjects.

Methods

All participants (n = 28) were supplemented with 6.4 g/day of BA for 23 days. The subjects were allocated to a control group, HV, or HI training group. During the BA supplementation period, the training groups performed nine exercise sessions, consisting of either 75–90 min continuous cycling at 35–45% W_max (HV) or 3 to 5 repeats of 30 s cycling at 165% W_max with 4 min recovery (HI). Carnosine content was measured in soleus and gastrocnemius medialis by proton magnetic resonance spectroscopy.

Results

There was no difference in absolute increase in carnosine content between the groups in soleus and gastrocnemius muscle. For the average muscle carnosine content, a higher absolute increase was found in HV (+2.95 mM; P = 0.046) and HI (+3.26 mM; P = 0.028) group compared to the control group (+1.91 mM). However, there was no additional difference between the HV and HI training group.

Conclusion

HV and HI exercise training showed no significant difference on BA-induced muscle carnosine loading in soleus and gastrocnemius muscle. It can be suggested that there can be a small cumulative effect of exercise on BA supplementation efficiency, although differences did not reach significance on individual muscle level.

Dysfunctional modulation of default mode network activity in attention-deficit/hyperactivity disorder

The state regulation deficit model posits that individuals with attention-deficit/hyperactivity disorder (ADHD) have difficulty applying mental effort effectively under suboptimal conditions such as very fast and very slow event rates (ERs). ADHD is also associated with diminished suppression of default mode network (DMN) activity and related performance deficits on tasks requiring effortful engagement. The current study builds on these 2 literatures to test the hypothesis that failure to modulate DMN activity in ADHD might be especially pronounced at ER extremes. Nineteen adults with ADHD and 20 individuals without any neuropsychiatric condition successfully completed a simple target detection task under 3 ER conditions (2-, 4-, and 8-s interstimulus intervals) inside the scanner. Task-related DMN deactivations were compared between 2 groups. There was a differential effect of ER on DMN activity for individuals with ADHD compared to controls. Individuals with ADHD displayed excessive DMN activity at the fast and slow, but not at the moderate ER. The results indicate that DMN attenuation in ADHD is disrupted in suboptimal energetic states where additional effort is required to optimize task engagement. DMN dysregulation may be an important element of the neurobiological underpinnings of state regulation deficits in ADHD.

Anticipatory processes in brain state switching - evidence from a novel cued-switching task implicating default mode and salience networks

The default mode network (DMN) is the core brain system supporting internally oriented cognition. The ability to attenuate the DMN when switching to externally oriented processing is a prerequisite for effective performance and adaptive self-regulation. Right anterior insula (rAI), a core hub of the salience network (SN), has been proposed to control the switching from DMN to task-relevant brain networks. Little is currently known about the extent of anticipatory processes subserved by DMN and SN during switching. We investigated anticipatory DMN and SN modulation using a novel cued-switching task of between-state (rest-to-task/task-to-rest) and within-state (task-to-task) transitions. Twenty healthy adults performed the task implemented in an event-related functional magnetic resonance imaging (fMRI) design. Increases in activity were observed in the DMN regions in response to cues signalling upcoming rest. DMN attenuation was observed for rest-to-task switch cues. Obversely, DMN was up-regulated by task-to-rest cues. The strongest rAI response was observed to rest-to-task switch cues. Task-to-task switch cues elicited smaller rAI activation, whereas no significant rAI activation occurred for task-to-rest switches. Our data provide the first evidence that DMN modulation occurs rapidly and can be elicited by short duration cues signalling rest- and task-related state switches. The role of rAI appears to be limited to certain switch types - those implicating transition from a resting state and to tasks involving active cognitive engagement.